Invasive Species Compendium

Detailed coverage of invasive species threatening livelihoods and the environment worldwide

CABI Book Chapter

Pest risk modelling and mapping for invasive alien species.

Book cover for Pest risk modelling and mapping for invasive alien species.


The International Pest Risk Mapping Workgroup acknowledges that advanced training and a 'tool kit' of software packages are needed to produce pest risk maps that are fully fit for purpose. This book is an initial attempt to address those needs. Invited chapters emphasize specific steps and data requirements to guide users through the development of pest risk models and maps, or components thereof....

Chapter 11 (Page no: 162)

Spatial modelling approaches for understanding and predicting the impacts of invasive alien species on native species and ecosystems.

Biological invasions threaten native species and ecosystems worldwide. Estimating the level of risk that an invasive alien species poses to native species across landscapes is important for prioritizing mitigation efforts. We describe a risk assessment approach that incorporates spatial heterogeneity in effects and illustrate this method by considering the risk that the red imported fire ant (Solenopsis invicta) presents to two native birds. The common ground-dove (Columbina passerina), an oviparous, ground-nesting species with altricial young that prefers open habitats, is more susceptible to impacts from fire ants than the swallow-tailed kite (Elanoides forficatus), which occupies closed-canopy forests, nests high in trees, is oviparous and has altricial young. Risk approaches that consider land scapes and that are spatially explicit are of particular relevance as remaining un-developed lands become increasingly un common, disjointed and more important for the management and recovery of native species and ecosystems.

Other chapters from this book

Chapter: 1 (Page no: 1) The challenge of modelling and mapping the future distribution and impact of invasive alien species. Author(s): Venette, R. C.
Chapter: 2 (Page no: 18) Mapping endangered areas for pest risk analysis. Author(s): Baker, R., Eyre, D., Brunel, S., Dupin, M., Reynaud, P., Jarošík, V.
Chapter: 3 (Page no: 35) Following the transportation trail to anticipate human-mediated invasions in terrestrial ecosystems. Author(s): Colunga-Garcia, M., Haack, R. A.
Chapter: 4 (Page no: 49) Simulation modelling of long-distance windborne dispersal for invasion ecology. Author(s): Parry, H. R., Eagles, D., Kriticos, D. J.
Chapter: 5 (Page no: 65) Using the MAXENT program for species distribution modelling to assess invasion risk. Author(s): Jarnevich, C. S., Young, N.
Chapter: 6 (Page no: 82) The NCSU/APHIS plant pest forecasting system (NAPPFAST). Author(s): Magarey, R. D., Borchert, D. M., Fowler, G. A., Hong, S. C.
Chapter: 7 (Page no: 97) Detecting and interpreting patterns within regional pest species assemblages using self-organizing maps and other clustering methods. Author(s): Worner, S., Eschen, R., Kenis, M., Paini, D., Saikkonen, K., Suiter, K., Sunil Singh, Vänninen, I., Watts, M.
Chapter: 8 (Page no: 115) Modelling the spread of invasive species to support pest risk assessment: principles and application of a suite of generic models. Author(s): Robinet, C., Kehlenbeck, H., Werf, W. van der
Chapter: 9 (Page no: 131) Estimating spread rates of non-native species: the gypsy moth as a case study. Author(s): Tobin, P. C., Liebhold, A. M., Roberts, E. A., Blackburn, L. M.
Chapter: 10 (Page no: 145) Predicting the economic impacts of invasive species: the eradication of the giant sensitive plant from Western Australia. Author(s): Cook, D. C., Sheppard, A., Liu Shuang, Lonsdale, W. M.
Chapter: 12 (Page no: 171) Process-based pest risk mapping using Bayesian networks and GIS. Author(s): Klinken, R. D. van, Murray, J. V., Smith, C.
Chapter: 13 (Page no: 189) Identifying and assessing critical uncertainty thresholds in a forest pest risk model. Author(s): Koch, F. H., Yemshanov, D.
Chapter: 14 (Page no: 206) Making invasion models useful for decision makers: incorporating uncertainty, knowledge gaps and decision-making preferences. Author(s): Yemshanov, D., Koch, F. H., Ducey, M.
Chapter: 15 (Page no: 223) Assessing the quality of pest risk models. Author(s): Venette, S. J.